Motion capture system with a motion capture element that uses two or more sensors to measure a single physical quantity, for example to obtain both wide measurement range and high measurement precision. For example, a system may combine a low-range, high precision accelerometer having a range of −24 g to +24 g with a high-range accelerometer having a range of −400 g to +400 g. Data from the multiple sensors is transmitted to a computer that combines the individual sensor estimates into a single estimate for the physical quantity. Various methods may be used to combine individual estimates into a combined estimate, including for example weighting individual estimates by the inverse of the measurement variance of each sensor. Data may be extrapolated beyond the measurement range of a low-range sensor, using polynomial curves for example, and combined with data from a high-range sensor to form a combined estimate.
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1. A motion capture system that combines sensors with different measurement ranges comprising a motion capture element comprising a memory; a plurality of sensors comprising at least two sensors that each measure the same physical quantity, wherein said physical quantity is equal to or is a function of one or more of a position, an orientation, a velocity, an acceleration, an angular velocity, or an angular acceleration of said motion capture element; a first communication interface; a microprocessor coupled with said memory, said plurality of sensors, and said first communication interface, wherein said microprocessor is configured to collect sensor data from said plurality of sensors, wherein said sensor data comprises a sensor value from each sensor of said plurality of sensors; store said sensor data in said memory; transmit said sensor data to a computer via said first communication interface; wherein each sensor of said at least two sensors has a measurement range comprising a closed interval between a lower measurable value and an upper measurable value, said measurement range having an interior comprising a set of measurable values that are strictly greater than said lower measurable value and strictly less than said upper measurable value; said measurement range associated with each sensor of said at least two sensors differs from the measurement range associated with at least one other sensor of said at least two sensors; wherein said computer is configured to receive said sensor data; calculate an individual sensor estimate of said physical quantity from said sensor value associated with each sensor of said at least two sensors; combine the individual sensor estimate across said at least two sensors to form a combined estimate of said physical quantity; analyze a motion of said motion capture element based on said sensor data and on said combined estimate of said physical quantity.
A motion capture system combines data from multiple sensors with different measurement ranges to improve accuracy and range. The system includes a motion capture device containing a memory, several sensors (at least two measuring the same physical property like position, orientation, velocity, acceleration, angular velocity, or angular acceleration), a communication interface, and a microprocessor. The microprocessor collects and stores sensor data, then transmits it to a computer. Each sensor has a specific measurement range with defined lower and upper limits, where these limits differ between the at least two sensors measuring the same physical quantity. The computer receives the sensor data, calculates individual estimates from each sensor, combines these estimates into a single, more accurate estimate, and then analyzes the motion of the capture device based on both the original sensor data and the combined estimate.
2. The system of claim 1 wherein said plurality of sensors comprises at least one rate gyroscope; said at least two sensors that each measure the same physical quantity comprise a plurality of accelerometers.
The motion capture system from the previous description includes at least one rate gyroscope and multiple accelerometers as its sensors. The accelerometers are used in pairs or multiples to measure the same acceleration, with different accelerometers having different measurement ranges. The system combines the data from these accelerometers to provide a more accurate and wider-range acceleration measurement than could be achieved with a single accelerometer.
3. The system of claim 2 wherein a first accelerometer in said plurality of accelerometers has an upper measurable value of 24 g or lower.
The motion capture system from the previous description includes a rate gyroscope, multiple accelerometers, where at least one of the accelerometers (a first accelerometer) has a relatively low measurement range, with an upper limit of 24 g (gravitational acceleration) or less. This accelerometer is likely used for high-precision measurements within its limited range. The system still combines the data from multiple accelerometers measuring the same acceleration.
4. The system of claim 3 wherein a second accelerometer in said plurality of accelerometers has an upper measurable value of 100 g or higher.
The motion capture system from the previous description includes a rate gyroscope, multiple accelerometers, where a first accelerometer has an upper measurable value of 24g or lower, and at least one other accelerometer (a second accelerometer) has a high measurement range, with an upper limit of 100 g or greater. The lower-range accelerometer provides high precision, while the higher-range accelerometer prevents data clipping during high-acceleration events. The system combines data from both to produce an accurate, wide-range estimate.
5. The system of claim 2 wherein a first accelerometer in said plurality of accelerometers has an upper measurable value of 16 g or lower.
The motion capture system from the previous description includes a rate gyroscope, multiple accelerometers, where at least one of the accelerometers (a first accelerometer) has a relatively low measurement range, with an upper limit of 16 g (gravitational acceleration) or less. This accelerometer is likely used for very high-precision measurements within its limited range. The system still combines the data from multiple accelerometers measuring the same acceleration.
6. The system of claim 5 wherein a second accelerometer in said plurality of accelerometers has an upper measurable value of 400 g or higher.
The motion capture system from the previous description includes a rate gyroscope, multiple accelerometers, where a first accelerometer has an upper measurable value of 16g or lower, and at least one other accelerometer (a second accelerometer) has a very high measurement range, with an upper limit of 400 g or greater. The lower-range accelerometer provides very high precision, while the higher-range accelerometer prevents data clipping during extreme acceleration events. The system combines data from both to produce an accurate, wide-range estimate.
7. The system of claim 1 wherein said combine the individual sensor estimate across said at least two sensors comprises determine whether the sensor value associated with each sensor of said at least two sensors is in said interior of said measurement range associated with said each sensor; when only one sensor value is in said interior of said measurement range, set said combined estimate of said physical quantity to said only one sensor value.
In the motion capture system described previously, the process of combining individual sensor estimates from at least two sensors involves checking if each sensor's value falls within its normal operating range (i.e., strictly between its minimum and maximum measurable values). If only one sensor's value is within its operating range, the system sets the combined estimate to that sensor's value, effectively using the valid sensor reading when the other sensors might be out of range or unreliable.
8. The system of claim 7 wherein said combine the individual sensor estimate across said at least two sensors further comprises when multiple sensor values are in said interior of said measurement range for the associated sensor, set said combined estimate of said physical quantity to a sensor value associated with a sensor that has a finest measurement resolution.
In the motion capture system described previously, the process of combining individual sensor estimates first checks if each sensor value is within its operating range. If multiple sensor values are within range, the system chooses the sensor with the finest measurement resolution (smallest difference between measurable values) and sets the combined estimate to that sensor's value, prioritizing the most precise measurement available.
9. The system of claim 7 wherein each sensor of said at least two sensors has an associated measurement variance; said combine the individual sensor estimate across said at least two sensors further comprises when multiple sensor values are in said interior of said measurement range for the associated sensor, set said combined estimate of said physical quantity to a weighted average of said multiple sensor values, with weights inversely proportional to said measurement variance for the associated sensor.
The motion capture system from the previous description combines sensor readings using a weighted average. Each of the at least two sensors measuring the same physical quantity has a known measurement variance (statistical measure of error). If multiple sensors provide readings within their valid measurement ranges, the system calculates a weighted average of these readings. The weight assigned to each sensor's reading is inversely proportional to its measurement variance, meaning sensors with lower variance (higher precision) have greater influence on the final combined estimate.
10. The system of claim 9 wherein said each sensor of said at least two sensors has an associated measurement resolution that represents a difference between successive measurement values of said each sensor; said measurement variance is proportional to a square of said measurement resolution.
The motion capture system from the previous description refines its weighting calculations based on measurement resolution. Each sensor has a measurement resolution, which is the smallest difference it can detect between two measurement values. The system calculates the measurement variance for each sensor (used in weighting the sensor data as described previously) by making the variance proportional to the square of the sensor's measurement resolution. A finer resolution implies a smaller variance and therefore a higher weight in the combined estimate.
11. The system of claim 1 wherein one or both of said computer and said microprocessor are further configured to track said sensor data over time; analyze said sensor data over time to determine whether one or more sensors of said at least two sensors are out of calibration; send a calibration required signal when said one or more sensors of said at least two sensors are out of calibration.
The motion capture system from the previous description includes functionality for sensor calibration monitoring. Either the computer or the microprocessor tracks sensor data over time and analyzes it to determine if any of the at least two sensors measuring the same physical quantity are drifting out of calibration. If the analysis detects that one or more sensors are out of calibration, the system sends a signal indicating that calibration is required.
12. The system of claim 11 wherein said analyze said sensor data over time comprises perform a paired t-test on sensor data samples, wherein each sensor data sample of said sensor data samples comprises a first sensor value associated with a first sensor of said at least two sensors, wherein said first sensor value is in said interior of said measurement range of said first sensor; a second sensor value associated with a second sensor of said at least two sensors, wherein said second sensor value is in said interior of said measurement range of said second sensor; wherein said first sensor value and said second sensor value were measured at substantially the same time.
In the motion capture system described previously, the process of analyzing sensor data over time to detect calibration issues uses a paired t-test. The system takes pairs of sensor values from the at least two sensors, ensuring that both values in each pair are within the sensors' normal operating ranges and were measured at approximately the same time. The paired t-test then statistically compares the two sets of sensor values to determine if there is a significant difference between them, which would indicate a calibration problem.
13. The system of claim 1 wherein said individual sensor estimate for a sensor of said at least two sensors is calculated as said sensor value when said sensor value is in said interior of said measurement range of said sensor; an extrapolated value based on extrapolation of one or more previous or subsequent sensor values in said interior of said measurement range when said sensor value is equal to said lower measurable value for said sensor or is equal to said upper measurable value for said sensor.
The motion capture system from the previous description handles situations where a sensor reading is at the edge of its measurement range by extrapolating values. If a sensor value is equal to the lower or upper measurable limit of the sensor, the system calculates an extrapolated value based on previous or subsequent sensor values that were within the sensor's normal measurement range. This extrapolated value is then used as the individual sensor estimate, extending the effective measurement range of the sensor. If the sensor value is within its normal measurement range, then that value is used as the individual sensor estimate.
14. The system of claim 13 wherein said extrapolation fits a polynomial curve to said one or more previous or subsequent sensor values.
In the motion capture system previously described, the extrapolation of sensor values at the range limits is achieved by fitting a polynomial curve to one or more prior or subsequent sensor values that fall within the sensor's normal measurement range. This polynomial curve is then used to estimate the sensor value that would have been measured had the sensor not reached its measurement limit. The system then combines estimates of different sensors.
15. The system of claim 13 wherein said combine the individual sensor estimate across said at least two sensors comprises set said combined estimate of said physical quantity to a weighted average of said multiple sensor values, wherein each individual sensor estimate has an associated weight; when said individual sensor estimate is said extrapolated value, set said associated weight for said extrapolated value to a decreasing function of a distance between said extrapolated value and said measurement range of said sensor.
The motion capture system from the previous description combines sensor data, including extrapolated values, using a weighted average. Each sensor reading has an associated weight. If a sensor reading is an extrapolated value (because the raw reading was at the sensor's range limit), the weight assigned to that extrapolated value is reduced based on how far the extrapolated value is from the sensor's normal measurement range. The further the extrapolated value is from the sensor's measurable range, the lower its weight in the final combined estimate.
16. The system of claim 15 wherein said associated weight for said extrapolated value is zero when said distance between said extrapolated value and said measurement range of said sensor exceeds a threshold.
In the motion capture system from the previous description, the weight assigned to extrapolated sensor values is reduced based on their distance from the sensor's measurement range. Specifically, if the distance between the extrapolated value and the sensor's normal measurement range exceeds a certain threshold, the weight assigned to that extrapolated value is set to zero, effectively discarding the extrapolated value from the final combined estimate because it is considered too unreliable.
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September 16, 2016
April 18, 2017
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